Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 3 |
| Since 2016 (last 10 years) | 3 |
| Since 2006 (last 20 years) | 3 |
Descriptor
| Artificial Intelligence | 3 |
| High School Students | 3 |
| Classification | 2 |
| Data Analysis | 2 |
| Decision Making | 2 |
| Models | 2 |
| Advanced Placement | 1 |
| Automation | 1 |
| Cognitive Processes | 1 |
| Computation | 1 |
| Computer Science Education | 1 |
| More ▼ | |
Author
| Chao, Jie | 3 |
| Jiang, Shiyan | 3 |
| Rosé, Carolyn P. | 3 |
| Finzer, William | 2 |
| Tang, Hengtao | 2 |
| Tatar, Cansu | 2 |
| Nocera, Amato | 1 |
| Qian, Yingxiao | 1 |
| Wiedemann, Kenia | 1 |
| Yalcinkaya, Rabia | 1 |
| Yoder, Michael Miller | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 3 |
Education Level
| High Schools | 3 |
| Secondary Education | 3 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkJiang, Shiyan; Qian, Yingxiao; Tang, Hengtao; Yalcinkaya, Rabia; Rosé, Carolyn P.; Chao, Jie; Finzer, William – Education and Information Technologies, 2023
As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Artificial Intelligence
Jiang, Shiyan; Tang, Hengtao; Tatar, Cansu; Rosé, Carolyn P.; Chao, Jie – Learning, Media and Technology, 2023
It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…
Descriptors: Artificial Intelligence, High School Students, Models, Classification
Jiang, Shiyan; Nocera, Amato; Tatar, Cansu; Yoder, Michael Miller; Chao, Jie; Wiedemann, Kenia; Finzer, William; Rosé, Carolyn P. – British Journal of Educational Technology, 2022
To date, many AI initiatives (eg, AI4K12, CS for All) developed standards and frameworks as guidance for educators to create accessible and engaging Artificial Intelligence (AI) learning experiences for K-12 students. These efforts revealed a significant need to prepare youth to gain a fundamental understanding of how intelligence is created,…
Descriptors: High School Students, Data, Artificial Intelligence, Mathematical Models
